Induction of decision trees using an internal control of induction

Authors:
Gonzalo Ramos-Jiménez;José del Campo-Ávila;Rafael Morales-Bueno
Affiliations:
Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Universidad de Málaga, Málaga, Spain;Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Universidad de Málaga, Málaga, Spain;Departamento de Lenguajes y Ciencias de la Computación, E.T.S. Ingeniería Informática, Universidad de Málaga, Málaga, Spain
Venue:
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Year:
2005

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Abstract

In this paper we present CIDIM (Control of Induction by sample DIvision Method), an algorithm that has been developed to induce small and accurate decision trees using a set of examples. It uses an internal control of induction to stop the induction and to avoid the overfitting. Other ideas like a dichotomic division or groups of consecutive values are used to improve the performance of the algorithm. CIDIM has been successfully compared with ID3 and C4.5. It induces trees that are significantly better than those induced by ID3 or C4.5 in almost every experiment.